ML, Recommandation engine, and so on.


  • recommendation engine
  • dimensionality reduction
    • topic modeling
    • feature similarity
    • types of link
    • multitude of relationships



  • current recommendation engine
    • inside as black box. naive approach based on correlation of user and user, user and items.
  • new approach
    • using deep semantics of relationship of items and users.
    • collect catalog of existing reviews
    • build network where node is item and relationship
      • substitute network: wine glass type A –> wine glass type B
      • complimentary network: wine glass –> wine refrigerator

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